Graduation Year

2024

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Biology (Cell Biology, Microbiology, Molecular Biology)

Major Professor

David Basanta, Ph.D.

Co-Major Professor

Shari Pilon-Thomas, Ph.D.

Committee Member

Heiko Enderling, Ph.D.

Committee Member

Joel Brown, Ph.D.

Committee Member

Sungjune Kim, M.D. Ph.D.

Committee Member

Thomas Yankeelov, Ph.D.

Keywords

Mathematical Modeling, Personalized Radiotherapy, Spatially Fractionated Radiotherapy, Tumor-immune interactions

Abstract

Tumor-immune interactions shape a developing tumor and its tumor immune microenvironment (TIME) resulting in either well-infiltrated, immunologically inflamed ‘hot’ tumor beds, or ‘cold’ immune deserts with low levels of infiltration. The pre-treatment immune state of the TIME is associated with treatment outcome; immunologically hot tumors generally exhibit better responses to radio- and immunotherapy than cold tumors. However, radiotherapy is known to induce opposing immunological consequences, resulting in both immunostimulatory and inhibitory responses. In fact, it is thought that the radiation induced tumoricidal immune response is curtailed by subsequent applications of radiation. Thus, I hypothesize that spatially fractionated radiotherapy (SFRT), administered through Grid blocks (SFRT-GRID) to create areas of low or high dose exposure, creates protective reservoirs of the tumor immune microenvironment, thereby preserving anti-tumor immune responses that are pivotal for radiation success. I developed an agent-based model (ABM) of tumor-immune interactions to investigate the immunological consequences and clinical outcomes after whole tumor radiation therapy (WTRT)and SFRT-GRID. The ABM is conceptually calibrated such that untreated tumors escape immune surveillance and grow to clinical detection. Individual ABM simulations are initialized from four distinct multiplex immunohistochemistry (mIHC) slides, and immune related parameter rates are generated using Latin Hypercube Sampling. In silico simulations suggest that direct radiation cell-kill alone is insufficient to clear a tumor with WTRT, however, explicit consideration of radiation induced antitumor immunity synergizes with radiation cytotoxicity to eradicate tumors. Similarly, the considered schedule of SFRT-GRID is successful with radiation induced antitumor immunity, and, for some pre-treatment TIME compositions and modeling parameters, SFRT-GRID might be superior to WTRT in providing tumor control. This study demonstrates the pivotal role of the radiation induced antitumor immunity. Prolonged fractionated treatment schedules may counteract early immune recruitment, which may be protected by SFRT-facilitated immune reservoirs. Different biological responses and treatment outcomes are observed based on pre-treatment TIME composition and model parameters. A rigorous analysis and model calibration for different tumor types and immune infiltration states is required before any conclusions can be drawn for clinical translation.

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